A Multi-Scale Analysis to set the Default Mode Network in noisy fMRI data

Abstract

Event Abstract Back to Event A Multi-Scale Analysis to set the Default Mode Network in noisy fMRI data Katherine Baquero1*, Francisco Gómez2, Andrea Soddu2, Audrey Vanhaudenhuyse2, Athena Demertzi2, Jean-Flory Tshibanda3, Olivia Gosseries2, Quentin Noirhomme2, Steven Laureys2 and Eduardo Romero1* 1 National University of Colombia, Biomedical Engineering, Colombia 2 University of Liege, Cyclotron Research Centre and Neurology Department, Belgium 3 University of Liege, CHU Sart Tilman Hospital, Belgium The Default Mode Network (DMN) is presently defined by those brain zones involved in maintaining a baseline brain activation. This network is usually revealed using Independent Component Analysis upon the fMRI data. However, a number of factors can easily perturb the acquired data, in particular a large head motion. Yet this problem has been partially overcome by registering the acquired brain volume, registration is still very limited in case of large head movements, a frequent scenario in patients with disorders of consciousness. This article presents a multiscale analysis of the fMRI data which improves the robustness with which the DMN is detected in subjects that move the head during the acquisition process. Initially, the method obtains multiple scales by filtering the original volumes out with a sequence of gaussian filters. Each fMRI scale is preprocessed by registering, normalizing, smoothing and coregistering, as described elsewhere, using the SPM software. These preprocessed data are then decomposed into the spatial-temporal components with the FastICA algorithm. The DMN is then selected with the Goodness of Fit approach (GoF), for each of the different scales. Finally, the components of the DMN at different scales are summed up, ruling out the original volume. The approach was validated by perturbing the acquired sequence of five healthy subjects with the six rigid-body movement series obtained from 15 subjects (5 Control, 3 Minimally Conscious State, 2 Locked in Syndrome and 5 Vegetative State), with head motion from 1mm up to 15 mm. In summary, the proposed method was applied to 18 disturbed data that lost the DMN, from which 11 fMRI data recovered the DMN. The mean of the Goodness of fit of the DMN component increased from 0.1 to 0.4. This multiscale analysis improves the robustness of the DMN detection in case of large head movements. Keywords: Computational Neurosciences, Default Mode Network, fMRI, High head motions, multiscale analysis Conference: BC11 : Computational Neuroscience & Neurotechnology Bernstein Conference & Neurex Annual Meeting 2011, Freiburg, Germany, 4 Oct - 6 Oct, 2011. Presentation Type: Abstract Topic: neurons, networks and dynamical systems (please use "neurons, networks and dynamical systems" as keywords) Citation: Baquero K, Gómez F, Soddu A, Vanhaudenhuyse A, Demertzi A, Tshibanda J, Gosseries O, Noirhomme Q, Laureys S and Romero E (2011). A Multi-Scale Analysis to set the Default Mode Network in noisy fMRI data. Front. Comput. Neurosci. Conference Abstract: BC11 : Computational Neuroscience & Neurotechnology Bernstein Conference & Neurex Annual Meeting 2011. doi: 10.3389/conf.fncom.2011.53.00067 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 23 Aug 2011; Published Online: 04 Oct 2011. * Correspondence: Miss. Katherine Baquero, National University of Colombia, Biomedical Engineering, Bogotá, Bogota DC, 11001000, Colombia, kabaquero@uliege.be Prof. Eduardo Romero, National University of Colombia, Biomedical Engineering, Bogotá, Bogota DC, 11001000, Colombia, edromero@unal.edu.co Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Katherine Baquero Francisco Gómez Andrea Soddu Audrey Vanhaudenhuyse Athena Demertzi Jean-Flory Tshibanda Olivia Gosseries Quentin Noirhomme Steven Laureys Eduardo Romero Google Katherine Baquero Francisco Gómez Andrea Soddu Audrey Vanhaudenhuyse Athena Demertzi Jean-Flory Tshibanda Olivia Gosseries Quentin Noirhomme Steven Laureys Eduardo Romero Google Scholar Katherine Baquero Francisco Gómez Andrea Soddu Audrey Vanhaudenhuyse Athena Demertzi Jean-Flory Tshibanda Olivia Gosseries Quentin Noirhomme Steven Laureys Eduardo Romero PubMed Katherine Baquero Francisco Gómez Andrea Soddu Audrey Vanhaudenhuyse Athena Demertzi Jean-Flory Tshibanda Olivia Gosseries Quentin Noirhomme Steven Laureys Eduardo Romero Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.